I evade. Do you? Compliance in groups and the effect of social proximity

Last registered on December 15, 2023

Pre-Trial

Trial Information

General Information

Title
I evade. Do you? Compliance in groups and the effect of social proximity
RCT ID
AEARCTR-0012570
Initial registration date
December 07, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
December 15, 2023, 4:00 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Region

Primary Investigator

Affiliation
University of Freiburg

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2023-12-11
End date
2023-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Collaborative tax evasion is a commonly observable problem, and examples such as the “LuxLeaks” or the “Panama Papers” are only two among many instances of such illegal collusive behavior. To counteract tax evasion and hence induce behavioral change, information provision about other anonymous individuals’ behavior is a recurring type of intervention. However, in accordance with previous research, it is plausible to assume that its use to promote tax compliance and thus fight tax evasion may backfire, when noncompliance is widespread. Further, due to the asymmetric effect of peer information, which describes individuals conforming solely with observed examples of peer’s non-compliance with a certain (informal) rule, it seems sensible to expose individuals to information about peers with whom they are especially socially proximate. So far, there are only few insights on the channels through which the effect of peer information works. Prior research in other domains however suggests, that social proximity between two partners may affect how information about their behavior affects own behavior. Further, empirical evidence suggests social proximity to allow to elicit responses to both compliance and violation of certain (informal) rules. I thus consider it crucial to shed light on the effect of social proximity with peers on collaborative tax evasion efforts.
Using an online sample, I run a randomized control trial in the form of a collaborative tax evasion game. The outcome of interest is the subjects’ tax compliance (income declaration rates of their company’s income). The random treatment assignment to one out of three treatments regarding information on social proximity with peers, the baseline (T1), social proximity (T2), and no social proximity (T3), is based on the subjects’ entry in the study’s experimental sessions.
Given a certain baseline level of compliance, I hypothesize social proximity to decrease the erosion of compliance, as individuals exposed to information on social proximity with their peers, will conform with peer’s compliance and noncompliance to a similar extent. However, I assume this effect to only hold in socially proximate groups and to be absent within non socially proximate groups.
External Link(s)

Registration Citation

Citation
Homa, Sofie. 2023. "I evade. Do you? Compliance in groups and the effect of social proximity." AEA RCT Registry. December 15. https://doi.org/10.1257/rct.12570-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-12-11
Intervention End Date
2023-12-31

Primary Outcomes

Primary Outcomes (end points)
I consider tax compliance rates (individual income declaration rate of company income), obtained from an online experiment, as primary outcomes of the study.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
I inquire the causal effect of social proximity with peers on tax compliance. I implement a collaborative online experiment, in which subjects recruited via a crowdsourcing platform, are asked to make corporate income declaration decisions.

The collaborative online experiment takes place in a corporate context and consists of various decision-making rounds. Participants are matched with a “colleague”, i.e., another participant of the same study. The group's task is to file their company's tax return. In each decision-making round participants must individually decide on what fraction of their company's income to declare, but the amount declared in the final tax report is the average of the group's individually declared incomes. The tax report is subject to being audited. The corporate income may vary with each round.

In the beginning of the collaborative online experiment subjects are randomly assigned to one out of three treatments. Participants in the first treatment (the baseline) are exposed to the behavior of their peer (previous income declaration decisions). In the second treatment participants are not only exposed to the behavior of their peer, but also to the information of being socially proximate with their peer. The third treatment resembles the second treatment expect for participants being exposed to the information of being non socially proximate with their peer.

The main outcome of interest is the subjects' tax compliance rates. Compliance behavior is translated from the income declaration decisions made by the subjects in various decisions rounds and allows to determine the inquired causal effect by introducing treatment dummy variables into the regression.
Experimental Design Details
Randomization Method
The random treatment assignment to one out of three treatments regarding information on social proximity with peers, the baseline (T1), social proximity (T2), and no social proximity (T3), is based on the subjects’ entry in one of the experimental sessions of the study. For each treatment, one experimental session is taking place. The entry in one of the experimental sessions is random, as subjects are free to choose when to take part in the online experiment after its implementation. Subjects' characteristics are assumed to be randomly distributed over the different experimental sessions.
Randomization Unit
Subjects taking part in the online experiment are randomly assigned to one out of three treatments based on their entry in one of the experimental sessions.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
I am planning on recruiting around 495 subjects to take part in the online experiment.
Sample size: planned number of observations
The planned number of observed income declaration decisions is 4950.
Sample size (or number of clusters) by treatment arms
A planned total amount of 495 subjects will be randomly assigned to one out of three treatment. Hence, 165 subjects are assigned to each of the three treatments. This results in 1650 observations per treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Gesellschaft für experimentelle Wirtschaftsforschung e.V. (GfeW)
IRB Approval Date
2023-12-07
IRB Approval Number
gkyauayL

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials